Equivalence of regression curves sharing common parameters

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dc.contributor.authorMöllenhoff, Kathrin
dc.contributor.authorBretz, Frank
dc.contributor.authorDette, Holger
dc.date.accessioned2019-02-14T15:31:27Z
dc.date.available2019-02-14T15:31:27Z
dc.date.issued2019
dc.description.abstractIn clinical trials the comparison of two different populations is a frequently addressed problem. Non-linear (parametric) regression models are commonly used to describe the relationship between covariates as the dose and a response variable in the two groups. In some situations it is reasonable to assume some model parameters to be the same, for instance the placebo effect or the maximum treatment effect. In this paper we develop a (parametric) bootstrap test to establish the similarity of two regression curves sharing some common parameters. We show by theoretical arguments and by means of a simulation study that the new test controls its level and achieves a reasonable power. Moreover, it is demonstrated that under the assumption of common parameters a considerable more powerful test can be constructed compared to the test which does not use this assumption. Finally, we illustrate potential applications of the new methodology by a clinical trial example.en
dc.identifier.urihttp://hdl.handle.net/2003/37915
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-19902
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;3/2019
dc.subjectsimilarity of regression curvesen
dc.subjectdose finding studiesen
dc.subjectnonlinear regressionen
dc.subjectparametric bootstrapen
dc.subjectequivalence testingen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.subject.rswkNichtlineare Regressionde
dc.subject.rswkBootstrap-Statistikde
dc.subject.rswkKlinisches Experimentde
dc.titleEquivalence of regression curves sharing common parametersen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access
eldorado.secondarypublicationfalsede

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Sonderforschungsbereich (SFB) 823